Introduction Phenols and parabens are ubiquitous environmental contaminants. Evidence from animal studies and limited human data suggest they may be endocrine disruptors. In the current study, we examined associations of phenols and parabens with reproductive and thyroid hormones in 106 pregnant women recruited for the prospective cohort, “Puerto Rico Testsite for Exploring Contamination Threats (PROTECT)”. Methods Urinary exposure biomarkers (bisphenol A, triclosan, benzophenone-3, 2,4-dichlorophenol, 2,5-dichlorophenol, butyl, methyl and propyl paraben) and serum hormone levels (estradiol, progesterone, sex hormone-binding globulin (SHBG), free triiodothyronine (FT3), free thyroxine (FT4) and thyroid stimulating hormone) were measured at up to two time points during pregnancy (16–20 weeks and 24–28 weeks). We used linear mixed models to assess relationships between exposure biomarkers and hormone levels across pregnancy, controlling for urinary specific gravity, maternal age, BMI and education. In sensitivity analyses, we evaluated cross-sectional relationships between exposure and hormone levels stratified by study visit using linear regression. Results An IQR increase in methyl paraben was associated with a 7.70% increase (95% CI 1.50, 13.90) in SHBG. Furthermore, an IQR increase in butyl paraben as associated with an 8.46% decrease (95% CI 16.92, 0.00) in estradiol, as well as a 9.34% decrease (95% CI −18.31, −0.38) in estradiol/progesterone. Conversely, an IQR increase in butyl paraben was associated with a 5.64% increase (95% CI 1.26, 10.02) in FT4. Progesterone was consistently negatively associated with phenols, but none reached statistical significance. After stratification, methyl and propyl paraben were suggestively negatively associated with estradiol at the first time point (16–20 weeks), and suggestively positively associated with estradiol at the second time point (24–28 weeks). Conclusions Within this ongoing birth cohort, certain phenols and parabens were associated with altered reproductive and thyroid hormone levels during pregnancy. These changes may contribute to adverse health effects in mothers or their offspring, but additional research is required.

Background: Prenatal exposure to certain xenobiotics has been associated with adverse birth outcomes. We examined the associations of triclocarban, phenols and parabens in a cohort of 922 pregnant women in Puerto Rico, the Puerto Rico Testsite for Exploring Contamination Threats Program (PROTECT). Methods: Urinary triclocarban, phenols and parabens were measured at three time points in pregnancy (visit 1: 16-20 weeks, visit 2: 20-24 weeks, visit 3: 24-28 weeks gestation). Multiple linear regression (MLR) models were conducted to regress gestational age and birthweight zscores against each woman's log average concentrations of exposure biomarkers. Logistic regression models were conducted to calculate odds of preterm birth, small or large for gestational age (SGA and LGA) in association with each of the exposure biomarkers. An interaction term between the average urinary biomarker concentration and infant sex was included in models to identify effect modification. The results were additionally stratified by study visit to look for windows of vulnerability. Results were transformed into the change in the birth outcome for an inter-quartile-range difference in biomarker concentration (Δ).

Certain phenols and parabens were associated with altered thyroid hormone levels during pregnancy, and the timing of exposure influenced the association between phenol and paraben, and hormone concentrations. These changes may contribute to downstream maternal and fetal health outcomes. Additional research is required to replicate the associations, and determine the potential biological mechanisms underlying the observed associations.

PurposeTo calculate the burden of lung cancer illness due to radon for all thirty-six health units in Ontario and determine the number of radon-attributable lung cancer deaths that could be prevented. MethodsWe calculated the population attributable risk percent, excess life-time risk ratio, life-years lost, the number of lung cancer deaths due to radon, and the number of deaths that could be prevented if all homes above various cut-points were effectively reduced to background levels.ResultsIt is estimated that 13.6 % (95 % CI 11.0, 16.7) of lung cancer deaths in Ontario are attributable to radon, corresponding to 847 (95 % CI 686, 1,039) lung cancer deaths each year, approximately 84 % of these in ever-smokers. If all homes above 200 Bq/m3, the current Canadian guideline, were remediated to background levels, it is estimated that 91 lung cancer deaths could be prevented each year, 233 if remediation was performed at 100 Bq/m3. There was important variation across health units.ConclusionsRadon is an important contributor to lung cancer deaths in Ontario. A large portion of radon-attributable lung cancer deaths are from exposures below the current Canadian guideline, suggesting interventions that install effective radon-preventive measures into buildings at build may be a good alternative population prevention strategy to testing and remediation. For some health units, testing and remediation may also prevent a portion of radon-related lung cancer deaths. Regional attributable risk estimates can help with local public health resource allocation and decision making.

Introduction Prenatal exposure to some phenols and parabens has been associated with adverse birth outcomes. Hormones may play an intermediate role between phenols and adverse outcomes. We examined the associations of phenol and paraben exposures with maternal reproductive and thyroid hormones in 602 pregnant women in Puerto Rico. Urinary triclocarban, phenol and paraben biomarkers, and serum hormones (estriol, progesterone, testosterone, sex-hormone-binding globulin (SHBG), corticotropin-releasing hormone (CRH), total triiodothyronine (T3), total thyroxine (T4), free thyroxine (FT4) and thyroid-stimulating hormone (TSH)) were measured at two visits during pregnancy. Methods Linear mixed models with a random intercept were constructed to examine the associations between hormones and urinary biomarkers. Results were additionally stratified by study visit. Results were transformed to hormone percent changes for an inter-quartile-range difference in exposure biomarker concentrations (%Δ). Results Bisphenol-S was associated with a decrease in CRH [(%Δ -11.35; 95% CI: -18.71, − 3.33), and bisphenol-F was associated with an increase in FT4 (%Δ: 2.76; 95% CI: 0.29, 5.22). Butyl-, methyl- and propylparaben were associated with decreases in SHBG [(%Δ: -5.27; 95% CI: -9.4, − 1.14); (%Δ: -3.53; 95% CI: -7.37, 0.31); (%Δ: -3.74; 95% CI: -7.76, 0.27)]. Triclocarban was positively associated with T3 (%Δ: 4.08; 95% CI: 1.18, 6.98) and T3/T4 ratio (%Δ: 4.67; 95% CI: -1.37, 6.65), and suggestively negatively associated with TSH (%Δ: -10.12; 95% CI: -19.47, 0.32). There was evidence of susceptible windows of vulnerability for some associations. At 24–28 weeks gestation, there was a positive association between 2,4-dichlorophenol and CRH (%Δ: 9.66; 95% CI: 0.67, 19.45) and between triclosan and estriol (%Δ: 13.17; 95% CI: 2.34, 25.2); and a negative association between triclocarban and SHBG (%Δ: -9.71; 95% CI:-19.1, − 0.27) and between bisphenol A and testosterone (%Δ: -17.37; 95% CI: -26.7, − 6.87). Conclusion Phenols and parabens are associated with hormone levels during pregnancy. Further studies are required to substantiate these findings. Electronic supplementary material The online version of this article (10.1186/s12940-019-0459-5) contains supplementary material, which is available to authorized users.

Objective We reviewed the literature on the association between pre-pregnancy multimorbidity (co-occurrence of two or more chronic conditions) and adverse maternal outcomes in pregnancy and postpartum. Data sources Medline, EMBASE, and CINAHL were searched from inception to September, 2021. Study selection Observational studies were eligible if they reported on the association between ≥ 2 co-occurring chronic conditions diagnosed before conception and any adverse maternal outcome in pregnancy or within 365 days of childbirth, had a comparison group, were peer-reviewed, and were written in English. Data extraction and synthesis Two reviewers used standardized instruments to extract data and rate study quality and the certainty of evidence. A narrative synthesis was performed. Results Of 6,381 studies retrieved, seven met our criteria. There were two prospective cohort studies, two retrospective cohort studies, and 3 cross-sectional studies, conducted in the United States (n=6) and Canada (n=1), and ranging in size from n=3,110 to n=57,326,681. Studies showed a dose-response relation between the number of co-occurring chronic conditions and risk of adverse maternal outcomes, including severe maternal morbidity or mortality, hypertensive disorders of pregnancy, and acute health care use in the perinatal period. Study quality was rated as strong (n=1), moderate (n=4), or weak (n=2), and the certainty of evidence was very low to moderate. Conclusion Given the increasing prevalence of chronic disease risk factors such as advanced maternal age and obesity, more research is needed to understand the impact of pre-pregnancy multimorbidity on maternal health so that appropriate preconception and perinatal supports can be developed.

Limit of detection (LOD) issues are ubiquitous in exposure assessment. Although there is an extensive literature on modeling exposure data under such imperfect measurement processes, including likelihood-based methods and multiple imputation, the standard practice continues to be naïve single imputation by a constant (e.g., JOURNAL/epide/04.03/00001648-201909000-00017/inline-graphic1/v/2023-09-08T093844Z/r/image-tiff ). In this article, we consider the situation where, due to the practical logistics of data accrual, sampling, and resource constraints, exposure data are analyzed in multiple batches where the LOD and the proportion of censored observations differ across batches. Compounding this problem is the potential for nonrandom assignment of samples to each batch, often driven by enrollment patterns and biosample storage. This issue is particularly important for binary outcome data where batches may have different levels of outcome enrichment. We first consider variants of existing methods to address varying LODs across multiple batches. We then propose a likelihood-based multiple imputation strategy to impute observations that are below the LOD while simultaneously accounting for differential batch assignment. Our simulation study shows that our proposed method has superior estimation properties (i.e., bias, coverage, statistical efficiency) compared to standard alternatives, provided that distributional assumptions are satisfied. Additionally, in most batch assignment configurations, complete-case analysis can be made unbiased by including batch indicator terms in the analysis model, although this strategy is less efficient relative to the proposed method. We illustrate our method by analyzing data from a cohort study in Puerto Rico that is investigating the relation between endocrine disruptor exposures and preterm birth.

Background Asthma is a risk factor for mental illness, but few studies have explored this association around the time of pregnancy. We studied the association between asthma and perinatal mental illness and explored the modifying effects of social and medical complexities. Methods In a population-based cohort of 846 155 women in Ontario, Canada, with a singleton live birth in 2005–2015 and no recent history of mental illness, modified Poisson regression models were constructed to examine the association between asthma diagnosed before pregnancy and perinatal mental illness, controlling for socio-demographics and medical history. We explored the modifying effects of social and medical complexities using relative excess risk due to interaction. Additional analyses examined the association between asthma and perinatal mental illness by timing and type of mental illness. Results Women with asthma were more likely than those without asthma to have perinatal mental illness [adjusted relative risk (aRR) 1.14; 95% (confidence interval) CI: 1.13, 1.16]. Asthma was associated with increased risk of diagnosis of mental illness prenatally (aRR 1.11; 95% CI: 1.08, 1.13) and post-partum (aRR 1.17; 95% CI: 1.15, 1.19) and specifically diagnoses of mood and anxiety disorders (aRR 1.14; 95% CI: 1.13, 1.16), psychotic disorders (aRR 1.20; 95% CI: 1.10, 1.31) and substance- or alcohol-use disorders (aRR 1.24; 95% CI: 1.14, 1.36). There was no effect modification related to social or medical complexity for these outcomes. Conclusions Women with asthma predating pregnancy are at slightly increased risk of mental illness in pregnancy and post-partum. A multidisciplinary management strategy may be required to ensure timely identification and treatment.